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apoorva
2025-06-19 13:23:04 +00:00
parent c8b3f3d587
commit 78c2ee2ff3
4 changed files with 15 additions and 5 deletions
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7
library/src/tensor_operation_instance/gpu/gemm_add/device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instance.cpp
View File

@@ -17,6 +17,9 @@ using S = ck::Sequence<Is...>;
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// e = elementwise((a * b), d0, d1)
// outout: e[m, n]
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
using device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_generic_instances = std::tuple<
// clang-format off
// M/N/K padding
@@ -24,8 +27,7 @@ using device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_generic_ins
//################################| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Stage| Size| Block| Block| Block| | WMMA| WMMA| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// TODO: these template variables need to be adjusted
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, BF16, BF16, F32, F32, BF16_Tuple, BF16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 8>, 8>
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, BF16, BF16, F32, F32, BF16_Tuple, BF16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 8>, 8>
// clang-format on
>;
@@ -36,7 +38,6 @@ using device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances =
//################################| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Stage| Size| Block| Block| Block| | WMMA| WMMA| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// TODO: these template variables need to be adjusted
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, BF16, BF16, F32, F32, BF16_Tuple, BF16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 2, S<1, 32, 1, 8>, 8, LoopScheduler::Default, PipelineVersion::v1>,
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, BF16, BF16, F32, F32, BF16_Tuple, BF16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 128, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 2, S<1, 32, 1, 4>, 8, LoopScheduler::Default, PipelineVersion::v1>,
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, BF16, BF16, F32, F32, BF16_Tuple, BF16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 128, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 2, S<1, 32, 1, 4>, 8, LoopScheduler::Default, PipelineVersion::v1>

5
library/src/tensor_operation_instance/gpu/gemm_add/device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
View File

@@ -17,6 +17,9 @@ using S = ck::Sequence<Is...>;
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// e = elementwise((a * b), d0, d1)
// outout: e[m, n]
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
using device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_generic_instances = std::tuple<
// clang-format off
// M/N/K padding
@@ -24,7 +27,6 @@ using device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_generic_instanc
//################################| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Stage| Size| Block| Block| Block| | WMMA| WMMA| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// TODO: these template variables need to be adjusted
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, F16, F16, F32, F32,F16_Tuple, F16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 2, S<1, 32, 1, 8>, 8>
// clang-format on
>;
@@ -36,7 +38,6 @@ using device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std
//################################| Layout| Layout| Layout| Layout| Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Stage| Size| Block| Block| Block| | WMMA| WMMA| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MWaveMPerXdl| ScalarPerVector|
//################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// TODO: these template variables need to be adjusted
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, F16, F16, F32, F32,F16_Tuple, F16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 256, 128, 128, 64, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 2, S<1, 32, 1, 8>, 8, LoopScheduler::Default, PipelineVersion::v1>,
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, F16, F16, F32, F32,F16_Tuple, F16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 128, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 2, S<1, 32, 1, 4>, 8, LoopScheduler::Default, PipelineVersion::v1>,
DeviceGemmMultipleD_Wmma_CShuffle< Row, Row, Row_Tuple, Row, F16, F16, F32, F32,F16_Tuple, F16, PassThrough, PassThrough, Add, GemmMNKPadding, 1, 128, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 2, S<1, 32, 1, 4>, 8, LoopScheduler::Default, PipelineVersion::v1>

4
library/src/tensor_operation_instance/gpu/gemm_add/device_gemm_add_wmma_c_shuffle_v3_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instance.cpp
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@@ -25,6 +25,10 @@ static constexpr auto V1 = BlockGemmPipelineVersion::v1;
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
template <GemmSpecialization GemmSpec>
// e = elementwise((a * b), d0, d1)
// outout: e[m, n]
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
using device_gemm_add_wmma_c_shuffle_bf16_bf16_bf16_bf16_mk_kn_mn_mn_instances = std::tuple<
// clang-format off
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|

4
library/src/tensor_operation_instance/gpu/gemm_add/device_gemm_add_wmma_c_shuffle_v3_f16_f16_f16_f16_mk_kn_mn_mn_instance.cpp
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@@ -25,6 +25,10 @@ static constexpr auto V1 = BlockGemmPipelineVersion::v1;
static constexpr auto V3 = BlockGemmPipelineVersion::v3;
template <GemmSpecialization GemmSpec>
// e = elementwise((a * b), d0, d1)
// outout: e[m, n]
// input: a[m, k], b[k, n], d0[m, n], d1[m, n]
using device_gemm_add_wmma_c_shuffle_f16_f16_f16_f16_mk_kn_mn_mn_instances = std::tuple<
// clang-format off
//##################################| ALayout| BLayout| DsLayout| ELayout| AData| BData| DsData| EData| AccData| CShuffle| A| B| CDE| GemmSpec| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CShuffleBlockTransfer| CDEShuffleBlockTransfer| BlkGemm| BlkGemm|